DeepLIFT [1]} is another backpropagation-based method. This method defines a reference point in the input space (similar to the baseline input for IntegratedGradients), and compares the activation of each neuron to its activation on the reference point (the “reference activation”). Attribution scores are then assigned according to that difference. We specifically use DeepLIFT with the Rescale rule (for more details, see [1]}). DeepSHAP [3]} extends the DeepLIFT algorithm to approximate Shapley values, by computing and averaging DeepLIFT attributions for multiple reference images.
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